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Renewable Energy and Power Quality Journal 2024年第3期22卷 118-131页

作者： Meng, Jiaxiao Du, Jinyan Liang, Zhihong Yang, Chunyan Jiang, Yixin Electric Power Research Institute CSG Guangdong Guangzhou China Guangdong Provincial Key Laboratory of Power System Network Security Guangdong Guangzhou China

With the sudden development in electronic and network technology, the power grid has emerged in several evolved nations and other areas with faster development. Energy storage can enhance the stability, resiliency and efficiency of the electric smart grid. The power grid transfers energy via bidirectional control of energy and information flow. In the power grid, a smart meter is an important component that is deployed on the user side to determine the consumption of energy regularly. However, the data about the usage of electricity leads to the leakage of the private information of the user, which threatens the privacy of the user. The attackers can change the in-transit message induce wrong information and sometimes cause disastrous action. Hence, it is important to assure data security and privacy of users by conducting authentication in power grid communication. An optimization technique named Puzzle Optimization Algorithm (POA) is designed for the efficient privacy-preserving aggregation approach with multi-factor authentication and a biometric scheme. Also, optimal key-based Elliptic Curve Cryptography (ECC) is used to encrypt the sensitive data that are securely stored. Authentication offers high security and texture analysis. In the registration phase, the privacy information of the person with their biometrics is the important feature point of the individual unique identification. Additionally, the designed approach is compared with other existing optimizations to analyse the functionality of the implemented technique. The simulation outcome defined that the suggested technique enhances user privacy and information security than other standard approaches. © 2024, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Biometric Scheme Multi-Factor Authentication Power Grid

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Training-free Graph Anomaly Detection: A Simple Approach via Singular Value Decomposition 25

Training-free Graph Anomaly Detection: A Simple Approach via...

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34th ACM Web Conference, WWW 2025

作者： Zhou, Cheng Li, Guangxia Weng, Hao Xiang, Yiyu Shaanxi Key Laboratory of Network and System Security Xidian University Xi’an China

ISBN: (纸本)9798400712746

Graph anomaly detection (GAD) is essential for identifying irregular behavior within graphs. Recent advances in GAD rely on deep learning techniques and have shown promise. However, prior deep learning-based GAD methods suffer from various limitations such as low accuracy, long training time, and limited scalability. To tackle these limitations, we propose TFGAD, a training-free graph anomaly detection approach. Our main idea is to process node attributes and local structures separately using distinct matrices, which are optimally determined via singular value decomposition, thus eliminating the need for additional training. For anomaly detection, we propose a lightweight scoring function that combines the reconstruction errors of node attributes with the projection lengths of local structures to quantify node abnormalities. Extensive experiments demonstrate that TFGAD significantly outperforms state-of-the-art deep learning-based baselines while reducing runtime and memory overhead. The results highlight TFGAD’s potential as an effective and efficient solution for GAD, particularly in scenarios where computational resources are constrained. © 2025 Copyright held by the owner/author(s).

关键词： Deep learning

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THL: Fast Targeted High Utility Itemset Mining within Length Consideration

Journal of Network Intelligence

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Journal of network Intelligence 2025年第1期10卷 541-558页

作者： Xu, Peiming Jiang, Yixin Kuang, Xiaoyun Luo, Yu Chen, Jiahui Guangdong Provincial Key Laboratory of Power System Network Security CSG Guangzhou510000 China School of Computer Science and Technology Guangdong University of Technology Guangzhou510006 China

High utility itemset mining is a research topic of the pattern mining domain, which has been widely applied in reality during the past decade. Although most high utility itemset mining algorithms show significant execution performance regarding runtime and memory usage, numerous results are useless for users. Targeted high utility itemset mining can reduce the number of high utility itemsets and improve the efficiency of pattern analysis. However, the targeted high utility itemset mining task aims to find targeted high utility itemsets with as many items as possible. Users are not that interested in long results in actual scenarios. Therefore, in this article, we first formulate the problem and then address this issue by proposing a new algorithm named THL for mining targeted high utility itemset within length constraints, based on utility list structure. Furthermore, to improve the performance of the novel algorithm, THL adopts several efficiency pruning strategies, including length and utility aspects. Finally, we conduct an extensive experimental evaluation to compare the SOTA algorithms with THL on several datasets. © 2025, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： data mining high utility itemset length constraint targeted items

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Locally differentially private high-dimensional data synthesis

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Science China(Information Sciences) 2023年第1期66卷 25-42页

作者： Xue CHEN Cheng WANG Qing YANG Teng HU Changjun JIANG Key Laboratory of Embedded System and Service Computing (Tongji University) Ministry of Education National (Province-Ministry Joint) Collaborative Innovation Center for Financial Network Security Tongji University

In local differential privacy(LDP), a challenging problem is the ability to generate highdimensional data while efficiently capturing the correlation between attributes in a dataset. Existing solutions for low-dimensional data synthesis, which partition the privacy budget among all attributes, cease to be effective in high-dimensional scenarios due to the large-scale noise and communication cost caused by the high dimension. In fact, the high-dimensional characteristics not only bring challenges but also make it possible to apply some technologies to break this bottleneck. This paper presents Sam Priv Syn for high-dimensional data synthesis under LDP, which is composed of a marginal sampling module and a data generation *** marginal sampling module is used to sample from the original data to obtain two-way marginals. The sampling process is based on mutual information, which is updated iteratively to retain, as much as possible,the correlation between attributes. The data generation module is used to reconstruct the synthetic dataset from the sampled two-way marginals. Furthermore, this study conducted comparison experiments on the real-world datasets to demonstrate the effectiveness and efficiency of the proposed method, with results proving that Sam PrivSyn can not only protect privacy but also retain the correlation information between the attributes.

关键词： local differential privacy high-dimensional data synthesis sampling data privacy privacy-preserving protocols

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Malicious Client Detection with Differential Privacy Constraints Based on Model Update Slicing and K-Means Clustering 6

Malicious Client Detection with Differential Privacy Constra...

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6th International Conference on Frontier Technologies of Information and Computer, ICFTIC 2024

作者： Qi, Mengshi Wang, Xin He, Yunpeng Yang, Ming Wu, Xiaoming Key Laboratory of Computing Power Network and Information Security Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250014 China

ISBN: (纸本)9798331541750

Federated learning (FL) is a decentralized machine learning technique that protects data privacy by trainng models locally on devices and sharing only model updates instead of raw data. However, FL also faces multiple security challenges. Clientside poisoning attacks can compromise global model training by injecting malicious updates. Additionally, the server may infer private information from client model updates. Most existing studies address these two risks separately, lacking a systematic analysis and response to their combined threats. This paper proposes a method called Sliced-Clustering Guard (SCGuard), which slices gradients and performs clustering analysis on each segment, enabling the server to more accurately detect malicious updates and effectively differentiate malicious client updates with differential privacy (DP) protection. Experimental results demonstrate that SCGuard can mitigate poisoning attacks while effectively safeguarding clients' sensitive information. © 2024 IEEE.

关键词： Federated learning

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Cross-chain Transaction Tracking Protocol based on Multi-dimensional Digital Watermarking Fingerprints 6

Cross-chain Transaction Tracking Protocol based on Multi-dim...

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6th International Conference on Frontier Technologies of Information and Computer, ICFTIC 2024

作者： Li, Duanzhen Xu, Shujiang He, Haochen Xue, Hongrui Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250014 China

ISBN: (纸本)9798331541750

Cross-chain technology plays a critical role in the process of interconnecting blockchains. However, all attention has been focused on how to achieve efficient cross-chain interoperability protocols, thus neglecting the most important security issues in cross-chain data interaction. Frequent network attacks and data privacy leaks have sounded the alarm for the safety of cross-chain data transactions. How to solve the problem of data ownership tracking in cross-chain transactions has become the top priority. This paper designs a cross-chain transaction tracking protocol based on multi-dimensional digital watermark fingerprints, using robust watermark, fragile watermark, and user identity key to achieve multi-dimensional tracking and supervision of cross-chain data transactions. Finally, this paper analyzes the feasibility and efficiency of the proposed protocol through experiments. © 2024 IEEE.

关键词： Blockchain

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STGAN: Detecting Host Threats via Fusion of Spatial-Temporal Features in Host Provenance Graphs 25

STGAN: Detecting Host Threats via Fusion of Spatial-Temporal...

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34th ACM Web Conference, WWW 2025

作者： Sang, Anyuan Fan, Xuezheng Yang, Li Wang, Yuchen Zhou, Lu Jia, Junbo Yang, Huipeng Xidian University Xi’an China Xidian University Shaanxi Key Laboratory of Network and System Security Xi’an China

ISBN: (纸本)9798400712746

As the complexity and frequency of cyberattacks, such as Advanced Persistent Threats (APTs) and ransomware, continue to escalate, traditional anomaly detection methods have proven inadequate in addressing these sophisticated, multi-faceted threats. Recently, Host Provenance Graphs (HPGs) have played a crucial role in analyzing system-level interactions, detecting anomalous behaviors, and tracing attack chains. However, existing provenance-based detection methods primarily rely on single-dimensional feature analysis, which fails to capture the dynamic and multi-dimensional patterns of modern APT attacks, resulting in insufficient detection performance. To overcome this limitation, we introduce STGAN, a model that integrates spatial-temporal graphs into host provenance graph modeling. STGAN applies temporal and spatial encoding to dynamic provenance graphs to extract temporal, spatial, and semantic features, constructing a comprehensive feature representation. This representation is further fused and enhanced using a multi-head self-attention mechanism, followed by anomaly detection. Through extensive evaluations on three widely-used provenance graph datasets, we demonstrate that our approach consistently outperforms current state-of-the-art techniques in terms of detection performance. Additionally, we contribute to the research community by releasing our datasets and code, facilitating further exploration and validation. © 2025 Copyright held by the owner/author(s).

关键词： Computer viruses

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Atomic transport dynamics in crossed optical dipole trap

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Chinese Physics B 2024年第7期33卷 293-301页

作者：彭鹏张正熙樊耀塬殷国玲毛德凯陈徐宗熊炜周小计 State Key Laboratory of Advanced Optical Communication System and Network School of ElectronicsPeking UniversityBeijing 100871China Institute of Carbon-based Thin Film Electronics Peking UniversityTaiyuan 030012China State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Opto-ElectronicsShanxi UniversityTaiyuan 030006China

We study the dynamical evolution of cold atoms in crossed optical dipole trap theoretically and experimentally. The atomic transport process is accompanied by two competitive kinds of physical mechanics, atomic loading and atomic *** loading process normally is negligible in the evaporative cooling experiment on the ground, while it is significant in preparation of ultra-cold atoms in the space station. Normally, the atomic loading process is much weaker than the atomic loss process, and the atomic number in the central region of the trap decreases monotonically, as reported in previous research. However, when the atomic loading process is comparable to the atomic loss process, the atomic number in the central region of the trap will initially increase to a maximum value and then slowly decrease, and we have observed the phenomenon first. The increase of atomic number in the central region of the trap shows the presence of the loading process, and this will be significant especially under microgravity conditions. We build a theoretical model to analyze the competitive relationship, which coincides with the experimental results well. Furthermore, we have also given the predicted evolutionary behaviors under different conditions. This research provides a solid foundation for further understanding of the atomic transport process in traps. The analysis of loading process is of significant importance for preparation of ultra-cold atoms in a crossed optical dipole trap under microgravity conditions.

关键词： cold atom crossed optical dipole trap transport process

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The Study of Multi-type Computing Power Trading Mechanism in Computing Power network Based on Blockchain and Combinatorial Double Auction 24

The Study of Multi-type Computing Power Trading Mechanism in...

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4th International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2024

作者： Zhao, Yue Wang, Jizhi Kong, Lingrui Sui, Tongtong Shandong Computer Science Center National Supercomputer Center in Jinan Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Provincial Key Laboratory of Industrial Network and Information System Security Qilu University of Technology Shandong Academy of Sciences Jinan Shandong China Quancheng Laboratory Jinan Key Laboratory of Digital Security Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Qilu University of Technology Shandong Academy of Sciences Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan Shandong China

ISBN: (纸本)9798400710247

The advancement of 5G and mobile internet technologies has propelled the development of emerging businesses and applications, demanding higher requirements for network bandwidth and computational resources. To address this challenge, the computing power network (CPN) has emerged. The CPN integrates computing and networking in depth, achieving collaborative allocation of distributed computing resources, enhancing the efficient utilization of computing resources, and improving user experiences in network services. However, in the development of fields such as Extended Reality (XR), Smart Healthcare, Connected Vehicles, and Artificial Intelligence (AI), there is a multidimensional, complex, and rapidly growing demand for computing resources. Therefore, it is crucial to establish a trading mechanism that integrates multiple computing resources in CPN. In this paper, a computing power trading scheme based on blockchain and combinatorial double auction is proposed. Firstly, a computing power trading system based on blockchain was designed, leveraging the decentralized and highly secure characteristics of blockchain technology to enhance the security of computing power transactions. Furthermore, a multi-type computing power trading mechanism (MCPT) based on blockchain and combinatorial double auction was introduced. The use of combinatorial double auctions as an incentive mechanism enables the trading of multiple computing power resources and results in high social welfare. Moreover, a discrete rime optimization algorithm (DRIME) is designed in the proposed mechanism (MCPT) to better solve the computing trading problem. Through simulation experiments, the effectiveness of the approach is validated. © 2024 Copyright held by the owner/author(s).

关键词： Computing power

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Gigahertz frequency hopping in an optical phase-locked loop for Raman lasers

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Chinese Physics B 2024年第2期33卷 60-65页

作者：毛德凯税鸿冕殷国玲彭鹏王春唯周小计 State Key Laboratory of Advanced Optical Communication System and Network School of ElectronicsPeking UniversityBeijing 100871China Institute of Carbon-based Thin Film Electronics Peking UniversityTaiyuan 030012China State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Opto-ElectronicsShanxi UniversityTaiyuan 030006China Institute of Advanced Functional Materials and Devices Shanxi UniversityTaiyuan 030031China

Raman lasers are essential in atomic physics,and the development of portable devices has posed requirements for time-division multiplexing of Raman *** demonstrate an innovative gigahertz frequency hopping approach of a slave Raman laser within an optical phase-locked loop(OPLL),which finds practical application in an atomic gravimeter,where the OPLL frequently switches between near-resonance lasers and significantly detuned Raman *** method merges the advantages of rapid and extensive frequency hopping with the OPLL’s inherent low phase noise,and exhibits a versatile range of applications in compact laser systems,promising advancements in portable instruments.

关键词： Raman lasers optical phase-locked loop frequency hopping

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